


The wide adoption of emulation and deployment testbeds 
 in the networking research community has spurred 
  studies on different approaches for designing and managing 
   networking research testbeds.
For example, the resource management mechanisms for Globus 
 and PlanetLab are contrasted and compared extensively by Ripeanu~\cite{GlobusPlanetLab}. 
Additionally,  Banik et. al~\cite{floorcontrol} conduct 
 empirical evaluations for different protocols that can provide exclusive 
  access to shared resources on PlanetLab.
The StarBED project has several unique solutions for emulation that include 
 configuring the testbed and providing mechanisms for experiment management~\cite{simpleTestBed, StartBED2}. 
 %es a \textit{floor control} problem (a problem of providing exclusive access to shared resources in collaborative applications), \cite{floorControl} presents 
%For example, how to configure testbeds using physical hardware~\cite{simpleTestBed}, 
% adopts an approach to prepare a configurable testbed using actual nodes
%technologies for deployment of software defined networks for flexible configurations~\cite{OpenRoads}, 
%describes the deployment of OpenRoads testbed at Stanford University, 
%and  shows design concepts, overall architecture and implemented functionalities of StarBED2\cite{StarBED2}. 
%In TORI \cite{TORI}, the authors extend testbeds towards a dynamic, peer-to-peer based environment.

The over scheduling and resource management of testbeds has becoming increasingly challenging.
Hermenier and Ricci examine the topological requirements 
 of the experiments on Emulab over the last fifteen years~\cite{Hermenier2012how}. 
 They investigate a variety of properties of experiment topologies 
and primarly propose two design enhancements: 1) increasing the heterogeniety of  node connectivity, and 2) spread out the  
 node and switch connectivity.  Their simulation results demonstrate promising improvements but require 
  significant changes to the underlying testbed hardware.
 % it is unlikely to carry out these methods in real scenario even within moderate time, since installing additional NICs and rewiring can take substantial downtime. 
 Kim et. al characterize the PlanetLab resource usage over the last decade~\cite{kim2011understanding}. 
Their results indicate that bartering and central banking schemes for resource allocation 
 can handle only a small percentage of total scheduling requirements. 
 They do not propose better resource allocation algorithms even though they identify  
  the factors that account for high resource contention or poor utilization. 
 % have been identified. Besides, federated nature of PlanetLab infrastructure limits the extensions of its operation and maintenance experience to dedicated testbeds like Deterlab and Emulab.
In this paper we first present a detailed analysis of the resource allocation challenges on DETERLab 
 and then propose an enhanced allocation and scheduling algorithm that does significantly better than the current mechanisms.

%More testbed operators aim at online measurement in real time, such as CPU usage, bandwidth, etc. \cite{OnlineMeasurement} develops a highly extensible measurement platform. A mostly-scalable monitoring system for PlanetLab is proposed in \cite{CoMon}. Vendetta \cite{Vendetta} integrates a GUI supporting 3D graphics, flexible monitoring and management into one single tool. Also, some peers \cite{meshnet} mine testbed usage statistics, including time spent in solving hardware and software related problems, traffic in MAC layer, boot time of machines, and so forth.

%Our work fundamentally distinguishes from above endeavors. The objective of this paper is to first 
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%lies in that we try to intercept the testbed usage from user behaviors, rather than operators and technical support representatives. The user behaviors consist of distribution of time that users spend on experiments, usage patterns of researcher and students and corresponding distinctions, relationships between testbed usage (time periods, times, experiment topologies, etc) and research outcomes (publications of high quality), and the like. Mining user behaviors can help us gain insights into strengths and weaknesses of testbeds, which further leads to targeted improvements making testbeds easier to use and more productive. We find a technical report \cite{PlanetLabUsage} on PlanetLab usage that is similar to our work, but their raw and simple statistics are far away from our goal. We believe our work contributes preliminary insights, if not first, into the user behavior analysis field in testbed environment.
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